def run_risk(self, cfg, hazard_id):
"""
Given the path to job config file, run the job and assert that it was
successful. If this assertion passes, return the completed job.
:param str cfg:
Path to a job config file.
:param int hazard_id:
ID of the hazard output used by the risk calculation
:returns:
The completed :class:`~openquake.engine.db.models.OqJob`.
:raises:
:exc:`AssertionError` if the job was not successfully run.
"""
completed_job = helpers.run_risk_job(cfg, hazard_output_id=hazard_id)
self.assertEqual('complete', completed_job.status)
return completed_job
def run_risk(self, cfg, hazard_id):
"""
Given the path to job config file, run the job and assert that it was
successful. If this assertion passes, return the completed job.
:param str cfg:
Path to a job config file.
:param int hazard_id:
ID of the hazard output used by the risk calculation
:returns:
The completed :class:`~openquake.engine.db.models.OqJob`.
:raises:
:exc:`AssertionError` if the job was not successfully run.
"""
completed_job = helpers.run_risk_job(cfg, hazard_output_id=hazard_id)
self.assertEqual('complete', completed_job.status)
return completed_job
def test_event_based_risk_export(self):
target_dir = tempfile.mkdtemp()
try:
haz_cfg = helpers.get_data_path(
'end-to-end-hazard-risk/job_haz_event_based.ini'
)
risk_cfg = helpers.get_data_path(
'end-to-end-hazard-risk/job_risk_event_based.ini'
)
haz_job = helpers.run_hazard_job(haz_cfg)
# Run the risk on all outputs produced by the haz calc:
risk_job = helpers.run_risk_job(
risk_cfg, hazard_calculation_id=haz_job.hazard_calculation.id
)
risk_outputs = models.Output.objects.filter(oq_job=risk_job)
agg_loss_curve_outputs = risk_outputs.filter(
output_type='agg_loss_curve')
loss_curve_outputs = risk_outputs.filter(output_type='loss_curve')
loss_map_outputs = risk_outputs.filter(output_type='loss_map')
# (1 mean + 2 quantiles) * 2 (as there also insured curves)
self.assertEqual(6, loss_curve_outputs.count())
# 16 rlzs + 16 (due to insured curves)
event_loss_curve_outputs = risk_outputs.filter(
output_type='event_loss_curve')
self.assertEqual(32, event_loss_curve_outputs.count())
self.assertEqual(16, agg_loss_curve_outputs.count())
# make sure the mean and quantile curve sets got created correctly
loss_curves = models.LossCurve.objects.filter(
output__oq_job=risk_job
)
# sanity check (16 aggregate loss curve + 38 loss curves)
self.assertEqual(54, loss_curves.count())
# mean
self.assertEqual(2, loss_curves.filter(statistics='mean').count())
# quantiles
self.assertEqual(
4, loss_curves.filter(statistics='quantile').count()
)
# 16 logic tree realizations = 16 loss map + 1 mean loss
# map + 2 quantile loss map
self.assertEqual(19, loss_map_outputs.count())
# 16 event loss table (1 per rlz)
event_loss_tables = risk_outputs.filter(output_type="event_loss")
self.assertEqual(16, event_loss_tables.count())
# 32 loss fractions
loss_fraction_outputs = risk_outputs.filter(
output_type="loss_fraction")
self.assertEqual(32, loss_fraction_outputs.count())
# Now try to export everything, just to do a "smoketest" of the
# exporter code:
loss_curve_files = []
for o in loss_curve_outputs:
loss_curve_files.append(risk.export(o.id, target_dir, 'xml'))
for o in event_loss_curve_outputs:
loss_curve_files.append(risk.export(o.id, target_dir, 'xml'))
agg_loss_curve_files = []
for o in agg_loss_curve_outputs:
agg_loss_curve_files.append(
risk.export(o.id, target_dir, 'xml')
)
event_loss_table_files = []
for o in event_loss_tables:
event_loss_table_files.append(
risk.export(o.id, target_dir, 'xml')
)
loss_map_files = []
for o in loss_map_outputs:
loss_map_files.append(risk.export(o.id, target_dir, 'xml'))
self.assertEqual(38, len(loss_curve_files))
self.assertEqual(16, len(agg_loss_curve_files))
self.assertEqual(16, len(event_loss_table_files))
self.assertEqual(19, len(loss_map_files))
for f in loss_curve_files:
self._test_exported_file(f)
for f in loss_map_files:
self._test_exported_file(f)
finally:
shutil.rmtree(target_dir)
def test_classical_risk_export(self):
target_dir = tempfile.mkdtemp()
try:
haz_cfg = helpers.get_data_path(
'end-to-end-hazard-risk/job_haz_classical.ini'
)
risk_cfg = helpers.get_data_path(
'end-to-end-hazard-risk/job_risk_classical.ini'
)
haz_job = helpers.run_hazard_job(haz_cfg)
# Run the risk on all outputs produced by the haz calc:
risk_job = helpers.run_risk_job(
risk_cfg, hazard_calculation_id=haz_job.hazard_calculation.id
)
risk_outputs = models.Output.objects.filter(oq_job=risk_job)
loss_curve_outputs = risk_outputs.filter(output_type='loss_curve')
loss_map_outputs = risk_outputs.filter(output_type='loss_map')
# 16 logic tree realizations + 1 mean + 2 quantiles = 19
# + 19 insured loss curves
self.assertEqual(38, loss_curve_outputs.count())
# make sure the mean and quantile curve sets got created correctly
loss_curves = models.LossCurve.objects.filter(
output__oq_job=risk_job,
insured=False
)
# sanity check
self.assertEqual(19, loss_curves.count())
insured_curves = models.LossCurve.objects.filter(
output__oq_job=risk_job,
insured=True
)
# sanity check
self.assertEqual(19, insured_curves.count())
# mean
self.assertEqual(1, loss_curves.filter(statistics='mean').count())
# quantiles
self.assertEqual(
2, loss_curves.filter(statistics='quantile').count()
)
# mean
self.assertEqual(
1, insured_curves.filter(statistics='mean').count())
# quantiles
self.assertEqual(
2, insured_curves.filter(statistics='quantile').count()
)
# 16 logic tree realizations = 16 loss map + 1 mean loss
# map + 2 quantile loss map
self.assertEqual(19, loss_map_outputs.count())
# 19 loss fractions
loss_fraction_outputs = risk_outputs.filter(
output_type="loss_fraction")
self.assertEqual(19, loss_fraction_outputs.count())
# Now try to export everything, just to do a "smoketest" of the
# exporter code:
loss_curve_files = []
for o in loss_curve_outputs:
loss_curve_files.append(risk.export(o.id, target_dir, 'xml'))
loss_map_files = []
for o in loss_map_outputs:
loss_map_files.append(risk.export(o.id, target_dir, 'xml'))
self.assertEqual(38, len(loss_curve_files))
self.assertEqual(19, len(loss_map_files))
for f in loss_curve_files:
self._test_exported_file(f)
for f in loss_map_files:
self._test_exported_file(f)
finally:
shutil.rmtree(target_dir)